Modularity analysis is a powerful tool for studying the design of biological networks, offering potential clues for relating the biochemical function(s) of a network with the 'wiring' of its components. Relatively little work has been done to examine whether the modularity of a network depends on the physiological perturbations that influence its biochemical state. Here, we present a novel modularity analysis algorithm based on edge-betweenness centrality, which facilitates the use of directional information and measurable biochemical data.

White adipose tissue (WAT) mass is the main determinant of obesity and associated health risks. WAT expansion results from increases in white adipocyte cell number and size, which in turn reflect a series of shifts in the cellular metabolic state. To quantitatively profile the metabolic alterations occurring during de novo adipocyte formation, metabolic flux analysis (MFA) was used in conjunction with a novel modularity analysis algorithm on differentiating 3T3-L1 preadipocytes. Use of a type I collagen gel as an effective long-term culture substrate was also assessed. The calculated flux distributions predicted the sequential activation of several intracellular cross-compartmental pathways, including lipogenesis, the pentose phosphate pathway, and the malate cycle, in good agreement with earlier isotopic tracer experiments and gene profiling studies. Partition of the adipocyte metabolic network into highly interacting reaction subgroups suggested a functional reorganization of the major pathways consistent with the lipid-loading phenotype of the adipocyte. Flux and modularity analysis results together point to the flux distribution around pyruvate as a key indicator of adipocyte lipid accumulation.

The liver is the major source of proteins used throughout the body for various functions. Upon injury or infection, an acute phase response (APR) is initiated in the liver that is primarily mediated by inflammatory cytokines such as interleukin-1beta (IL-1beta) and interleukin-6. Among others, the APR is characterized by an altered protein synthetic profile. We used two-dimensional gel electrophoresis to study the dynamics of changes in protein synthesis in hepatocytes exposed to these inflammatory cytokines. Protein profiles were quantified using image analysis and further analyzed using multivariate statistical methods. Our results indicate that IL-1beta and IL-6 each induces secreted protein responses with distinct dynamics and dose-dependence. Parallel stimulation by IL-1beta and IL-6 results in a protein pattern indistinguishable from the IL-1beta pattern, indicating a dominant effect of IL-1beta over IL-6 at the doses tested. Multidimensional scaling (MDS) of correlation distances between protein secretion levels revealed two protein pairs that are robustly co-secreted across the various cytokine stimulation conditions, suggesting shared regulatory pathways. Finally, we also used multivariate alternating conditional expectation (MACE) to identify transformation functions that discriminated the cytokine-stimulated and untreated hepatocyte-secreted protein profiles. Our analysis indicates that the expression of neutrophil gelatinase-associated lipocalin (NGAL) was sufficient to discriminate between IL-1beta and IL-6 stimulation. The combination of proteomics and multivariate analysis is expected to provide new information on the cellular regulatory networks involved in generating specific cellular responses.

Motivation: The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Results: Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for topdown partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage.

Sepsis is an important cause of death in very-low-birth-weight (VLBW) neonates. Although conventional diagnostic indicator of sepsis has been done by blood cultures, this took much longer time. The measurement of platelet-associated parameters such as mean platelet volume (MPV) and platelet distribution width (PDW) become more reliable and accurate parameters as a non-specific marker for sepsis. Our objective is to examine the usefulness of those platelet hematological parameters as a supplementary diagnostic tool for sepsis in VLBW infants. This study is a retrospective cohort study of neonates subject to the diagnosis of sepsis from October 2006 to July 2010. This study was conducted at Korea University medical center. We studied total 2,336 infants for 32 days from birth (Day 0) to Day 31. We compared three groups of infants to examine differences of platelet parameters according to their age from birth to Day 31: (i) full-terms versus VLBW without sepsis, (ii) VLBW without sepsis versus VLBW with sepsis and (iii) thrombocytopenic VLBW without sepsis versus those with sepsis. The platelet-associated parameters were significantly distinguishable between septic and non-septic groups at their early age (∼ 1 week), especially platelet counts (PLT) (p = 0.0091), MPV (p = 0.007) and PDW (p = 0.0372) in thrombocytopenic VLBW infants. The decreased PLT, elevated MPV and PDW were major characteristics of septic group. We suggested maximum cutoff values of the platelet factors by performing receiver operating characteristic curve analysis between septic and non-septic thrombocytopenic VLBW infants, among which MPV was the most promising index (AUCMPV = 0.7044 > AUCPLT = 0.6921 > AUCPDW = 0.6593). Platelet-associated hematological parameters are useful for the early diagnosis of sepsis as a more efficient and supplementary diagnostic method in thrombocytopenic VLBW infants.